What is Online Analytical Processing? (OLAP in ERP)

Having accurate and timely information is essential to making sound decisions in business. That’s where OLAP in ERP comes in.

Online Analytical Processing helps businesses analyze data quickly and efficiently to get a clear picture of what’s going on in their company and make the right choices for the future.

This blog post will discuss OLAP, its types, and other details.

Definition

Online analytical processing (OLAP) is a type of database used for data analysis. It allows users to view data in different ways and analyze it differently. It is typically used for reporting and analysis, and companies can track trends over time.

It is also known as multidimensional databases because they allow users to view the data in multiple dimensions.

What is OLAP in ERP?

OLAP is a process used to analyze data quickly and efficiently. It allows businesses to examine their data in multiple dimensions to understand what’s happening within their company. This can help with making informed decisions about the future of the company.

It is often used in conjunction with ERP software. ERP systems contain a lot of data that can be difficult to analyze manually. It helps to make this data more manageable and accessible.

How does it work?

For example, it provides time series and trend analysis views. To analyze data, it collects data from multiple data sources, stores data in data warehouses, and again organizes data in the form of an OLAP cube.

The chief component of online analytical processing is the OLAP server, which sits between a client and a database management system (DBMS), and which understands how data is organized in the database and has special functions for analyzing the data.

There are OLAP servers available for nearly all the major database systems.

It is more important to know about the Online analytical processing cube. The OLAP cube is a data structure that allows you to analyze data quickly.

The cube classifies numerical facts (measures) by dimensions. Multidimensional data is stored and analyzed in this cube.

Online Analytical Processing Cube

Advantages of Online Analytical Processing

  • It helps to get all the data together to create accurate and quick information about the business. 
  • It helps to analyze the time series
  • Provides a platform for all types of business, including planning, budgeting, forecasting, financial reporting, and data warehouse reporting
  • Allows users to do compatible calculations
  • Allows users to divide a big cube into dice cube data by several dimensions, measures, and filters. 
  • It helps the end-users to analyze data in multiple dimensions so that they make better decisions in business.

Disadvantages of Online Analytical Processing

  • It is challenging to have many dimensions in a single OLPA cube
  • The snowflake schema required for organizing data is complex to implement
  • Modification of a cube requires a complete update of the cube that consumes more time

Analytical operations in OLAP

Generally, it has four basic analytical operations.

Roll-up operation

It is also called ‘aggregation.’ We can perform this operation in two ways.

  • Reduction of dimension: It is the system in which the cube reduces its dimension
  • Climbing up concept hierarchy. It is the system of grouping things based on their level.
OLAP operations
Roll Up on Geography from cities to country

The above image shows the roll-up operation.

  • Here cities, New York and Washington rolled up into the USA
  • The sales figures of the cities were 400 and 550 and became 950 after rolled up

Drill-down operation

It is the opposite process of roll-up. It performs in 2 ways.

  • Increasing of dimension
  • Climbing down the concept hierarchy
Drill down operation
Drill Down on time(From Quarter to Month)

This image shows the drill-down operation

  • Quarter 1 is divided into months January, February, and March
  • Months dimension is added

Slice and dice operation

In a slice method, one dimension is chosen, and a subcube is generated. Two or more dimensions are selected in a dice operation, and subcubes are generated.

Slice and Dice Operation

Pivot operation

To provide a substitute presentation of data, you need to rotate the data axes in this operation.

Pivot Operation

When do you use online analytical processing?

You can use it in the following situations.

  • When you are required to perform complex analytical and ad hoc quickly without interrupting and affecting the OLTP system
  • When you need to issue reports using your data to the business users in an easy way
  • When you want to deliver several aggregations to help the user with consistent and quick results

What are the main types of Online Analytical Processing?

Types of OLAP

Three main types of Online analytical processing are

  1. Relational OLAP (ROLAP): In this type, data is stored in a relational database. It allows us to analyze multidimensional data. With this, data accuracy is very high. It offers expandability. That means it manages a large amount of data even when the data is increasing. Some disadvantages are also there with this type. It requires more manpower, hardware, and software. It has the lowest query performance system.
  2. Multidimensional OLAP (MOLAP) is a cube-based, multidimensional array of structured data storage. In this system, computation is high-speed.
  3. Hybrid OLAP (HOLAP): This is the combination of relational and multidimensional. Hence in this system, expandability is more, and computation is fast. It stores aggregated data in a multidimensional cube and detailed information in a relational database.

Apart from these three main types, some other types are below.

Web (WOLAP): This is based on a web browser. In this, the application is available by the web browser. It is a three-tier architecture that includes a database server, client, and interface.

This application does not require deployment in the client’s system. It requires only a web browser and a network connection.

Desktop (DOLAP): This is installed on the user’s desktop. It includes a client application and server.

The advantage of this type is that it offers better performance because the data is located near the user. The disadvantage is that it needs more storage space on the user’s computer.

Mobile (MOLAP): It is used to process data on mobile devices. In this, the engine resides on a mobile device such as a smartphone or tablet.

Spatial (SOLAP): This is used to process spatial data. In this, the engine resides on a server.

Some of its features are mapping, proximity searches, and routing.

What are OLAP tools?

These tools are the software that helps perform the slicing and dicing of data.

Following are the key features of the tools.

  • Ability to support parallelism
  • Front end flexibility
  • Powerful metadata layer
  • Good Performance
  • Security

Best OLAP software

  • Microstrategy
  • Microsoftpower BI
  • Google cloud flatform
  • Apache kylin
  • SAP AG
  • Operations Hub
  • pentaho BI
  • icCube

Difference between OLAP and OLTP

What is OLTP?

OLTP (Online Transaction Processing) systems are designed to meet this demand, providing companies with a fast and effective way to conduct transactions through the internet.
Whether it’s ordering products or making payments, OLTP systems are designed to get the job done quickly and efficiently. In many cases, OLTP is the primary function of an ERP system.
However, businesses can also choose to include OLAP capabilities to help them analyze their data. OLAP allows businesses to examine their data in various ways, providing valuable insights that can be used to improve operations and make better business decisions.
When it comes to online transaction processing, OLTP and OLAP provide a powerful one-two punch that can help any business take its operations to the next level.

OLAPOLTP
It is the system used for data analysis.It is the system used for data transactions.
A large amount of data identifies it.It is identified by a large number of small amounts of data.
It is large in size, basically ranging from 1Tb to 100Pb.It is small in size ranging from 1Mb to 10 Gb.
It operates with a data warehouse.It operates with a traditional database management system.
Its processing speed is less.It has a faster processing speed.
Its reply time is more, usually takes seconds to minute to respond.It responds quickly and takes only milliseconds.
It needs only read operations.It needs both read and write operations.
Its objective is to make decisions with the help of large data sources.Its objective is day-to-day operations.
Queries are complex.Queries are simple.
User strength is low (Its database allows only hundreds of users).User strength is high (Its database allows thousands of users).
It helps to improve the productivity of business analysts.It helps to improve the productivity and self-service of users.
It is created for business analysis.It is created for real-time business operations.

Conclusion

OLAP is a process used to analyze data quickly and efficiently. It allows businesses to examine their data in multiple dimensions to understand what’s happening within their company.

This can help with making informed decisions about the future of their company.

It is often used with ERP software, making data management more accessible and more efficient. As a result, it can be a valuable tool for businesses of all sizes.

If you’re looking to grow your business, it’s essential to have accurate data at your fingertips.

OLAP can help you do just that!

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